Порівняльний аналіз становлення Інклюзивної вищої освіти в україні та закордоном
Bibliographic record
Abstract
The article deals with inclusive education as the main and the most effective form of quality education for students with special needs. Education gives such students the opportunity to realize their fundamental rights, including education, work, self-fulfillment and integration into society. The regulatory framework for the research problem has been studied. The world experience in the field of inclusive education implementation, in particular in higher education and implementation in the educational system of Ukraine has been analyzed. The best experience of inclusive education implementation, including that of Italy, Canada, the USA, Czech Republic, Poland, has been identified. The achievements of the Ukrainian higher educational institutions, including the experience of the Ukrainian Catholic University, Open International University of Human Development «Ukraine», Ihor Sikorsky Kyiv Polytechnic University, Pavlo Tychyna Uman State Pedagogical University, are summarized. A generalized complex of methods that are required to create an inclusive educational environment has been offered, including the implementation of organizational support for a school leaver with special educational needs from the time of entering the university. Considerable attention should be paid to adaptation of entrance examinations according to the nosology and the needs of the entrant as well as to architectural accessibility in universities, including the availability of ramps, lifts, specially equipped sluice rooms, and parking spaces. These methods also include: corps marking with special colored arrows, and duplicating of writings with the Braille script for students with bad sight, use of sign interpreters assistance and audio-visual aids, creating a distance learning system for students who are unable to attend school due to health reasons, involvement of students with special educational needs into extracurricular activities, participation in projects and competitions with the aim of their better adaptation and development of their scientific and creative potential.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.013 | 0.005 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".